lkml.org 
[lkml]   [2016]   [Apr]   [29]   [last100]   RSS Feed
Views: [wrap][no wrap]   [headers]  [forward] 
 
Messages in this thread
/
From
SubjectRe: random(4) changes
Date
Am Freitag, 29. April 2016, 14:02:48 schrieb George Spelvin:

Hi George,

> >> 1. It DOES depend on the attacker. Any statement about independence
> >>
> >> depends on the available knowledge.
> >>
> >> 2. XOR being entropy preserving depends on independence ONLY, it does
> >>
> >> NOT depend on identical distribution. The latter is a red herring.
> >> (An English metaphor for "irrelevant distraction.")
> >>
> >> 3. Precisely because the bits are not independent, XOR is not
> >>
> >> guaranteed to be entropy-preserving (your sense) on real data.
> >
> > It seems we talk past each other. Your entire explanation refers to
> > individual bits that come in sequentially where the attacker inbetween
> > can analyze it and potentially modify his attack. Sure, in this case
> > they are not independent and I am not claiming that.
>
> You can analyze it in two equivalent ways:
>
> 1. The attacker knows all previous timestamps, and we are tring to
> quantify their uncertainty about the current timestamp word.
>
> In this case, some of the attacker's knowledge will be about
> correlations between the bits of that word.
>
> I think this is the easier way to think about the problem and
> the formulation I prefer. Especially because of the structure
> of the work you do afterward, XORing those 32 bits.
>
> 2. An attacker knows all previous *bits*, and is presented with, and
> tries to guess, the 32 bits of the timestamp one at a time.
>
> In this case, information gleaned from previously-seen bits which
> would be called correlations in option 1 get incorporated into the
> predicted distribution of the current bit.
>
> For measuring the source entropy, this is also a valid way to
> proceed. It's like Shannon's early studies of the entropy of
> English by letting readers read the first half of a novel and then
> asking them to guess what follows, one letter at a time.
>
> I think this form is less convenient in general, and it's particularly
> annoying when subsequently computing the parity of a word, as it's
> hard to talk about cancellations due to non-independent bits.
>
> Entropy (Shannon, Renyi, and min-) is additive, meaning that the two
> different ways of measuring will produce the same result.
>
> Either way, word or bit at a time, we are trying to quantify the *new*
> additional entropy contributed by the current sample. That means
> we assume for the analysis of each sample that all previous samples
> are known to the attacker.
>
> > But one single time stamp is one value where the entire 32 bits are
> > generated in an atomic fashion to any observer -- there is no sequential
> > obtaining of its bits, analyzing it and then reacting on it.
>
> I never suggested doing it any other way, although as I explained above
> it's possible to do so.
>
> I was only considering processing *words* sequentially.
>
> Knowledge of the previous *words* affect the predicted distribution
> of individual bits in the current word.

That is all correct what you write and I concur. But you still do not answer
the point I am making. You always in all your descriptions compare two or more
time stamps. And I always concured that they are dependent -- and XOR will do
whatever to the entropy.

What I am saying that the bits in one given time stamp are mutually
independent. I.e. bit 0 of one time stamp does not depend on bit 1 of that
very same time stamp.

I totally agree with you that bit 0 from time stamp 1 may tell you something
about bit 0 of time stamp 2. And therefore I am not considering multiple time
stamps for this first step.

Let me quote the definitions from SP800-90B:

IID: A sequence of random variables for which each element of the sequence has
the same probability distribution as the other values and all values are
mutually independent.

Independent: Two discrete random variables X and Y are (statistically)
independent if the probability that an observation of X will have a certain
value does not change, given knowledge of the value of an observation of Y
(and vice versa). When this is the case, the probability that the observed
values of X and Y will be x and y, respectively, is equal to the probability
that the observed value of X will be x (determined without regard for the
value of y) multiplied by the probability that the observed value of Y will be
y (determined without regard for the value of x).


All I am claiming and all I am saying is that the bits 0 through 31 in one
given time stamp are mutually indpendent. And thus the XOR of those
independent bits is appropriate.

>
> When woring word-at-a-time like this, we also have to consider
> cross-correlations among the bits of a word. The most general way to

Tell me where the correlations should be within one word. Where do you claim
they come from?

> express it is a set of 2^32 probabilities for each of the 2^32 possible
> values. The awkwardness of this form is why it's sometimes useful to
> think about smaller pieces.
>
> For example, if p(9) = 0.5, p(10) = 0.5, and p(x) = 0 for all other x,
> then we have 1 bit of entropy in the word.
>
> We can analyze it bit a time, and proceed in oe of two ways:
>
> - If we go lsbit first, then we have 1 bit of entropy in bit 0, but
> then zero entropy in bit 1.
> - If we go msbit first, we have 1 bit of entropy in bit 1, but then
> zero entropy in bit 0.

This description makes no sense.
>
> Either way, there's only 1 bit of entropy total because of the
> correlation between the bits. Once we have seen one of the bits, the
> entropy of the second one collapses to 0.

Again, where does the correlation is supposed to come from?
>
> And either way, we have 1 bit of entropy in the word, but 0 bits of entropy
> in the parity of the word.






Ciao
Stephan

\
 
 \ /
  Last update: 2016-04-29 21:01    [W:0.068 / U:0.344 seconds]
©2003-2020 Jasper Spaans|hosted at Digital Ocean and TransIP|Read the blog|Advertise on this site